1. Field of the Invention
This invention relates to vehicle manufacturing and systems for managing its administration and distribution. More particularly, the invention relates to computerized tools for receiving, summarizing, organizing, and balancing vehicle order requests among a plurality of manufacturing plants and re-sellers.
2. General Background and State of the Art
Automobile dealers make a variety of demands for vehicle models, options, and colors. These demands can vary according to time of year, consumer trends, and geographic location. In stocking their lots, automobile dealers are usually limited to the capacities of the manufacturer to produce certain vehicle configurations. Although they can make requests to modify their orders, there is no guarantee that dealers' requests will be fulfilled.
One example of a manufacturing plant's inability to fulfill specific dealer requests on shipment orders comprises limitations or constraints on the production of a certain vehicle model. Such constraints may be the result of a shortage of parts production limitations of the particular manufacturing plant. The constraints on manufacturing plant production in turn limit what can be shipped to dealers.
Due to such limitations, there has been a problem in matching manufacturing plant vehicle productions with consumer and dealer demands and requests. Typical methods for dealing with this problem in the past have involved requiring dealers to construct their requests as a function of manufacturing plant capabilities in lieu of, or in addition to, consumer demand. That is, auto dealers typically receive a suggested order from the manufacturer, or corporate office, which details the contents of the future shipment to the dealer's lot. Once the detailed order arrives at the dealer, it is reviewed by a manager or other employee, who can then make changes to the order. These changes are handled by the manufacturer, but without a guarantee that the changes can actually be accommodated.
This process is very time consuming and inefficient. Moreover, it does not ensure that the problem of matching manufacturing plant output with consumer demand and dealer requests is fully resolved, because there is no mechanism for ensuring that the dealer's annotations will be adhered to or dealt with by the manufacturer. For the dealers, the process is inconvenient and time consuming. Also, because there is no specific or consistent formula for granting these requests to the dealers, the method often produces results that are unfair from the perspective of the dealers. Overall, the result is a time consuming system that has difficulty matching dealers' preferences and demand for vehicles with the manufacturing plant's resources and availability.
Other current methods for matching dealer preferences with manufacturing plant resources and availability include computer assisted calculations for balancing dealer orders among a plurality of manufacturing plants. Ideally, the dealer orders would be consolidated and re-divided into manufacturing plant orders. The manufacturing plant orders would be optimally balanced and distributed among the plurality of manufacturing plants such that, as a minimum requirement toward achieving optimization, each manufacturing plant assigned a manufacturing plant order would be capable of manufacturing and producing the assigned manufacturing plant order. Additional goals commensurate with optimization of manufacturing plant order balancing would include minimizing shipping costs from manufacturing plants to dealers. Unfortunately, current computer assisted methods do not adequately handle dealer requests, and the resulting manufacturing plant order balancing is not optimized.
An example of a dealer request that cannot be handled by current methods for matching dealer preferences with manufacturing plant output involves vehicle emission type. California requires a specific emission type, which is different from the emission types allowed in the other 49 states. Current methods for matching dealer requests to manufacturing plant output do not yield consistent results. As a result, current methods frequently result in manufacturing plant orders including certain emission types to be assigned to the incorrect manufacturing plants, in zones where the emission type is inapplicable or unsupported. In these cases, users of systems operating these methods are required to modify the manufacturing plant orders by hand, which is an inefficient and time-consuming step. Of course, this problem is not limited to vehicle emission type. Rather, it is a widespread problem in the industry, and effects a plurality of vehicle options.
Yet another problem that is common with current systems and methods for matching dealer requests with manufacturing plant production capabilities is the manpower required to administer them. Current methods for balancing a set of dealer orders among a plurality of manufacturing plants involve (1) constructing a combined order model comprising all of the dealer orders (2) dividing the combined order model into component order models and (3) distributing the component order models among multiple system operators during processing. As part of the balancing calculations, the multiple system operators review results of the component order models and modify them by hand. The final result of processing the combined order model is achieved only after each of the component order models is completely processed, including hand-modifications made by each of the multiple system operators. The results of the component order model processing can then be assembled into the final result representing processing of the combined order model. These methods require the multiple system operators to run the system and wait for their component outputs at the same time. Thus, system operators are dependent on each other, and the end result is dependent on all of the system operators. Therefore, these systems and methods are inefficient and require substantial manpower to administer.
In the prior art method of FIG. 1, for example, the lot size balancing process begins at block 100, where a computer program, the “M.O.V.E.” program, is executed to generate a unit table for the allocation that will eventually result from the process. The unit table identifies available manufacturing plants and will, eventually, store data representing manufacturing plant orders that have been transformed from received dealer requests. Each manufacturing plant order is considered a unit within the unit table.
The procedure continues at block 102, where a balance is performed by executing a second computer program, the balance program, to generate a plant production order based on the unit table. Specifically, the plant production schedule is an allocation of received dealer requests or orders among a plurality of manufacturing plants identified in the unit table. The allocation is calculated by the second computer program by forcing the plant production order to conform to lot size rules at each individual manufacturing plant as well as to any production constraints that apply to those manufacturing plants. Lot size rules may include, for example, minimum or maximum limitations on production numbers of vehicles of a certain type. A group of vehicles sharing a common type is considered a lot. Production constraints may result from, for example, manufacturing plant inventory, manufacturing plant production capabilities, and the like.
Next, at block 104, the preliminary production order generated at block 102 undergoes a manual examination. At this point, users such as corporate employees may inspect and modify the preliminary plant production order. Such modifications may be made, for example, for sales or production planning purposes. Following any modifications that occur in this step, a third computer program, a spreadback program, is executed at block 106 to force changes made to the preliminary plant production order to be reflected in the unit table as a revised production order.
The revised production order is sent to automobile dealers at block 108 as a suggested production order. At this step, dealers have an opportunity to review the suggested production order and recommend or request changes to account for demand not reflected in the original allocation but later identified by the dealers. This step may occur multiple times as change requests are received from a plurality of dealers.
The modified production order is then subjected to the balance program a second time, at block 110. Once the production schedule is re-balanced, corporate employees have a second opportunity to inspect the production schedule and make manual changes at block 112. Any changes are forced into the production order via the spreadback program at block 114. Finally, a plant program computer program is executed, at block 116. The plant program assigns a manufacturing plant to each unit in the unit table containing the production schedule.
Clearly, this method results in a number of inefficiencies including a great amount of processing time, several instances of manual user input and, therefore, significant manpower requirements for administering the process. These drawbacks are the result of the general processing algorithm used by this method. Generally speaking, the M.O.V.E. program receives the results of the allocation process as input, and prepares a plant production schedule which closely approximates the results of the allocation while observing lot size rules and constraints that apply at the manufacturing plant that will build the units requested in the allocation. Specifically, the balance program divides the desired quantity of vehicles into groups according to attribute type. Therefore, each member vehicle of a group shares the same attribute type. Each group is then considered by itself, regarding conformity to lot size rules and manufacturing plant constraints. After the balance routine is run for groups according to one attribute type, the allocation is regrouped according to the next attribute type. In this manner, the balancing procedure is applied recursively, by attribute type, each time the balance program is run. Unfortunately, this inefficient method of balancing creates the need for multiple instances of manual user input to re-adjust the balancing results during the process. Moreover, the result is that vehicle manufacturers offer for sale only those vehicles that they have built, which are not necessarily the vehicles that customers want.